Modelo de ruteo para recolección de leche cruda usando algoritmos genéticos
DOI:
https://doi.org/10.18046/syt.v12i31.1916Palabras clave:
Modelo de ruteo, métodos metaheurísticos, algoritmos genéticos.Resumen
El artículo presenta la utilización de un método metaheurístico –algoritmos genéticos– para la evaluación de un modelo de rutas de recolección de leche cruda. Se implementó un modelo a partir de datos reales, recolectados por medio de trabajo de campo, siguiendo el método del «problema del agente viajero», usando el toolbox de algoritmos genéticos de Matlab®. Los resultados evidencian que las rutas obtenidas con la implementación del algoritmo genético son viables en cuanto a tiempo y nodos visitados, lo que demuestra el potencial de esta herramienta. Los costos obtenidos por este método difieren de los actuales en alrededor de 3%, valor que está dentro de los márgenes reportados en la literatura.Referencias
Alegre, J., Laguna, M., & Pacheco, J. (2007). Optimizing the periodic pick-up of raw materials for a manufacturer of auto parts. European Journal of Operational Research, 179(3), 736-746.
Baker, B. M., & Ayechew, M.A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5) 787-800.
Berger, J., & Barkaoui, M. (2003). A new hybrid genetic algorithm for the capacitated vehicle routing problem. The Journal of the Operational Research Society, 54(12), 1254-1262.
Claassen, G. D. & Hendriks, T.B. (2007). An application of special ordered sets to a periodic milk collection problem. European Journal of Operational Research, 180(2), 754-769.
Coene, S., Arnout, A., & Spieksma, F. (2008). The periodic vehicle routing problem: a case study [working paper]. Retrieved from http://www.econ.kuleuven.be/public/n05012/
Duarte, A. (2007). Metaheurísticas. Madrid: Dykinson.
García-Najera, A. & Bullinaria, J. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287.
Hemmelmayr, V., Doerner, K.F., Hartl, R.F., & Savelsbergh, M.W. (2009). Delivery strategies for blood products supplies. OR spectrum, 31(4), 707-725.
Jozefowiez, N., Sernet, F., & Talbi, E.-G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.
Larrañaga, P., Kuijpers, C.M.H., Murga, R.H., Inza, I., & Dizdarevic, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13(2), 129-170.
Laudon, K.C., & Laudon, J.P. (2004). Sistemas de información gerencial: administración de la empresa digital. (trans. A. Núñez). México DF: Pearson.
Lei, H.-T. & Guo, B. (2010). Comments on "An improved model for vehicle routing problem with time constraint based on genetic algorithm”. Computers & Industrial Engineering, 59(3), 479-480.
Maroto, C., Alcaraz, J., & Ruiz, R. (2002). Investigación operativa: modelos y técnicas de optimización. Valencia: Universidad Politécnica de Valencia.
Nagata, Y., Bräysy, O., & Dullaert, W. (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 37(4), 724-737.
Oppen, J. & Lokketangen, A. (2008). A tabu search approach for the livestock collection problem. Computers & Operations Research, 35(10), 3213-3229.
Panapinun, K. & Charnsethikul, P. (2005). Vehicle routing and scheduling problems: A case study of food distribution in greater Bangkok [working paper]. Retrieved from
http://ieinter.eng.ku.ac.th/research/optimization/pan04a.pdf
Robusté, F. & Galván, D. (2005). e-logistics. Barcelona: Universidad Politécnica de Catalunya.
Sigurd, M., Pisinger, D., & Sig, M. (2004). Scheduling transportation of live animals. Transportation Science, 38(2), 197-209.
Sterzik, S. & Kopfer, H. (2013). A tabu search heuristic for the inland container transportation problem. Computers and Operations Research, 40(4), 953-962.
Tarantilis, C. D., & Kiranoudis, C. T. (2005). Operational research and food logistics. Journal of Food Engineering, 70(3), 253-255.
Vansteenwegen, P., Souffriau, W., & Sörensen, K. (2010). Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated ARC routing with soft time windows. Computers and Operations Research, 37(11), 1870-1876.
Baker, B. M., & Ayechew, M.A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5) 787-800.
Berger, J., & Barkaoui, M. (2003). A new hybrid genetic algorithm for the capacitated vehicle routing problem. The Journal of the Operational Research Society, 54(12), 1254-1262.
Claassen, G. D. & Hendriks, T.B. (2007). An application of special ordered sets to a periodic milk collection problem. European Journal of Operational Research, 180(2), 754-769.
Coene, S., Arnout, A., & Spieksma, F. (2008). The periodic vehicle routing problem: a case study [working paper]. Retrieved from http://www.econ.kuleuven.be/public/n05012/
Duarte, A. (2007). Metaheurísticas. Madrid: Dykinson.
García-Najera, A. & Bullinaria, J. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287.
Hemmelmayr, V., Doerner, K.F., Hartl, R.F., & Savelsbergh, M.W. (2009). Delivery strategies for blood products supplies. OR spectrum, 31(4), 707-725.
Jozefowiez, N., Sernet, F., & Talbi, E.-G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.
Larrañaga, P., Kuijpers, C.M.H., Murga, R.H., Inza, I., & Dizdarevic, S. (1999). Genetic algorithms for the travelling salesman problem: A review of representations and operators. Artificial Intelligence Review, 13(2), 129-170.
Laudon, K.C., & Laudon, J.P. (2004). Sistemas de información gerencial: administración de la empresa digital. (trans. A. Núñez). México DF: Pearson.
Lei, H.-T. & Guo, B. (2010). Comments on "An improved model for vehicle routing problem with time constraint based on genetic algorithm”. Computers & Industrial Engineering, 59(3), 479-480.
Maroto, C., Alcaraz, J., & Ruiz, R. (2002). Investigación operativa: modelos y técnicas de optimización. Valencia: Universidad Politécnica de Valencia.
Nagata, Y., Bräysy, O., & Dullaert, W. (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 37(4), 724-737.
Oppen, J. & Lokketangen, A. (2008). A tabu search approach for the livestock collection problem. Computers & Operations Research, 35(10), 3213-3229.
Panapinun, K. & Charnsethikul, P. (2005). Vehicle routing and scheduling problems: A case study of food distribution in greater Bangkok [working paper]. Retrieved from
http://ieinter.eng.ku.ac.th/research/optimization/pan04a.pdf
Robusté, F. & Galván, D. (2005). e-logistics. Barcelona: Universidad Politécnica de Catalunya.
Sigurd, M., Pisinger, D., & Sig, M. (2004). Scheduling transportation of live animals. Transportation Science, 38(2), 197-209.
Sterzik, S. & Kopfer, H. (2013). A tabu search heuristic for the inland container transportation problem. Computers and Operations Research, 40(4), 953-962.
Tarantilis, C. D., & Kiranoudis, C. T. (2005). Operational research and food logistics. Journal of Food Engineering, 70(3), 253-255.
Vansteenwegen, P., Souffriau, W., & Sörensen, K. (2010). Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated ARC routing with soft time windows. Computers and Operations Research, 37(11), 1870-1876.
Descargas
Publicado
2014-12-23
Número
Sección
Reportes de caso
Licencia
Esta publicación está licenciada bajo los términos de la licencia CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.es)
